This disclosure relates to methods and apparatus to determine the required weather data and weather source sufficient to meet the operational or business constraints for a user or airspace environment.
Weather information (including wind, temperature, and turbulence) is one of the key factors of advanced air traffic management concepts. Typically, weather information is not uniformly applied to aircraft in flight. In many cases, no weather information is available, there is a multitude of viable weather data from multiple sources available, or the weather data, when available, is too old to be relevant or lacks the granularity needed to allow the flight management system to provide accurate predictions.
Weather assimilation and modeling systems such as NOAA's Rapid Refresh provide weather forecast data. This system represents and serves as a one potential source of forecasted weather data, but does not isolate the weather applicable to a flight trajectory. A system that does a projection of weather over a flight trajectory would be NOAA's Aviation Digital Data Service application, but it does not function outside the United States, and does not evaluate weather from multiple sources or evaluate weather against the needs or requirements of a user or an airspace.
Current solutions for obtaining weather generally use forecast weather applicable to a large region and the forecast weather information is updated at relatively long intervals when compared against events in a flight trajectory. For example, a typical aircraft descending from an altitude of 33,000 feet takes 20-25 minutes to reach the airport, whereas the forecast weather information is updated in 30-minute, 1-hour or 3-hour intervals from data recorded in the previous time interval. Therefore, weather for one segment of the flight might not be applicable to other segments. Some attempts have been made to achieve higher resolution and quicker updates of forecast weather, but those are generally applicable to a very small area, and introduce inaccuracies due to processing limitations. This also assumes an instantaneous delivery of the weather data to the recipient. For instance, for a forecast weather model produced every 30 minutes, at the time the processing is complete, the weather forecast is already 15-30 minutes old. Next, the time to transmit the data, receive the data by recipient, and finally process the received data must be considered for accuracy. This process can take an additional 30 minutes for a total of 1 hour from the time of the forecast, which directly impacts the accuracy when compared to actual weather readings.
Data fusion or data assimilation of the weather information may also be performed, but is not in a user-preferred manner that allows different smoothing and filtering techniques to be applied, or that takes a normalized timeline into account. Moreover, the weather within the most applicable volume around the trajectory is often not analyzed in the applicable time, which may lead to inaccurate results.
U.S. Pat. No. 8,332,084 (the disclosure of which is incorporated by reference herein in its entirety) discloses systems and methods for integrating and interpolating disparate weather information from multiple weather data sources in order to determine an effect of the disparate weather information on an aircraft's trajectory, such as on a planned trajectory, a current trajectory, or an intent trajectory. The system disclosed in U.S. Pat. No. 8,332,084 may further predict an updated trajectory of an aircraft or may provide an optimized alternate trajectory. By using highly accurate four-dimensional trajectory predictions, comprising the (X,Y,Z) coordinate location of the aircraft over the aircraft's trajectory versus time, combined with multiple weather data sources (e.g., Rapid Refresh, Automatic Dependent Surveillance-Contract, Mode S, or other types of weather data sources), projecting and associating the weather data sources in time, and applying smoothing techniques, a high level of accuracy in the weather data over the four-dimensional trajectory may be obtained. This data may be manipulated by using user-input configuration preferences, by using weighted analysis, and by applying error-corrected aircraft trajectory information, to determine a more accurate, updated four-dimensional trajectory of the aircraft. The error-corrected aircraft trajectory information may be continuously updated and adjusted as the flight of the aircraft progresses. This may allow for highly accurate four-dimensional trajectory projections.
In order to determine the effects of weather on an aircraft's trajectory, a user (e.g., an airline operator, air traffic controller, flight plan service) typically receives disparate weather information by subscribing to multiple weather data sources. Given a multitude of forecasted and in-situ weather information, it would be advantageous to have the capability to determine the “best” weather information that meets operational, performance or cost requirements for a particular subscriber or subscribers given a set of forecast and in-situ weather data. As used herein, the term “subscriber” means any internal or external system, service or user making a request to or receiving from the system. The system publishes the weather information as directed by the user or system configuration. In this case, the “best” weather information is defined as the weather data from a multitude of weather data sources that is as close as possible to actual weather. Currently all weather data sources build their weather data package using forecasted weather data. The “best” weather information defaults to data provided from the weather source where no actual determination is made of the best weather for that given operational, performance or cost requirement. Weather solutions are then built based on this weather data package, which may not meet subscriber operations and requirements. This problem is magnified in a situation where in-situ weather data is available. In-situ weather data is generally assumed to be “best”, which may not be true if it does not meet the subscriber operations and requirements.
There is a need for systems and methods for processing forecasted and in-situ weather data from multiple sources at varying times and with different resolutions for the purpose of determining which data and data sources are sufficient for subscriber needs.